Name: Handbook of High-Frequency Trading and Modeling in Finance
ISBN: 9781118443989

Book information

Authors: Ionut Florescu verified identity, Maria C. Mariani verified identity, H. Eugene Stanley verified identity, Frederi G. Viens verified identity
First published: 2016
Editions known: 4
Publishers: Wiley
Languages: eng
ISBN-13: 9781118443989, 9781118593486
Main topics: High-Frequency Trading
Also covers: Risk Management, Options and Volatility, Portfolio Optimization
Related site topics: High-Frequency Trading & Optimal Execution, Options & Derivatives Pricing, Portfolio Optimization, Risk Management & Tail Risk, Volatility Modeling & Forecasting

Overview

Handbook of High-Frequency Trading and Modeling in Finance is a book by Ionut Florescu, Maria C. Mariani, H. Eugene Stanley and Frederi G. Viens, first published in 2016. In this catalogue it is classified mainly under High-Frequency Trading, with secondary coverage of Risk Management, Options and Volatility and Portfolio Optimization.

Audience and depth. The available metadata did not allow a mathematical difficulty estimate, so none is shown; treat the technical level as unknown.

Orientation. The theory-versus-practice balance could not be determined from metadata. The archive holds 6 papers whose topics and vocabulary overlap with this book; those links are inferred (see the research connections below).

How to read this page. Topics, difficulty, prerequisites and orientation are model-derived (rule-based, rule_based_v1) from bibliographic metadata such as title, subject headings and edition data. They were not produced by reading the book and are not a review. Relevance confidence is 78% and difficulty confidence is 0%; the catalogue lists no ratings or awards.

Research assessment

Rule-based and model-derived from metadata (title, subject headings, edition data). These are not reviews or ratings; see the evidence below.

Quant-finance relevance	63/100 confidence 78% Score 63.3/100. Strongest: quant_relevance 0.96, metadata_completeness 0.85; weakest: practical_applicability 0.00. Evidence: title:'high-frequency trading', openalex_topics:'volatility modeling'. Difficulty unknown (neutral technical_depth).
Mathematical difficulty	Unknown
Metadata quality	70%

Difficulty evidence (1 signal)

stochastic_processes matched in openalex_topics: “stochastic processes”

Research connections

Related papers on this site

Similarity of research area (shared vocabulary, topics and methods). Not citations: the paper does not necessarily cite this book.

Modeling and Simulation of Financial Returns under Non-Gaussian Distributions Topic similarity inferred similarity 0.47
Measuring tail risk at high-frequency: An $L_1$-regularized extreme value regression approach with unit-root predictors Topic similarity inferred similarity 0.45
A high-frequency approach to Realized Risk Measures Topic similarity inferred similarity 0.44
Sizing Strategies for Algorithmic Trading in Volatile Markets: A Study of Backtesting and Risk Mitigation Analysis Topic similarity inferred similarity 0.43
Probabilistic Predictions of Option Prices Using Multiple Sources of Data Topic similarity inferred similarity 0.41
Extended State-dependent Hawkes Process for Limit Order Books: Mathematical Foundation and the Reproduction of Volatility Signature Plots Topic similarity inferred similarity 0.39

Similar books

High-Frequency Trading Models inferred similarity 0.42
High-Frequency Trading and Probability Theory inferred similarity 0.41
All about high-frequency trading inferred similarity 0.40
High-Frequency Trading inferred similarity 0.39
Algorithmic and High-Frequency Trading inferred similarity 0.37

Author profiles

Ionut Florescu verified identity
Maria C. Mariani verified identity
H. Eugene Stanley verified identity
Frederi G. Viens verified identity

External resources

Open Library
DOI
Search on Amazon (ISBN-13 9781118593486) (search link; may be an affiliate link)

Relationship graph

Solid lines are verified facts (authorship from persistent identifiers, editions); dashed lines are inferred by rules or similarity. Open in the full explorer.

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